Method for quantitatively revealing starting amount of grain size deformation mechanism

Abstract

The invention discloses a method for quantitatively revealing the starting amount of a grain size deformation mechanism, and belongs to the technical field of finite element simulation of microcosmic plastic deformation and crystal plasticity. According to the method, in-situ / quasi-in-situ electron back scattering diffraction characterization and crystal plasticity finite element simulation are combined, real grain initial orientation distribution and grain shape evolution information are obtained through experiments and introduced into a finite element model, and accurate quantitative analysis of deformation mechanisms such as slippage and twinning is achieved. Compared with a traditional method, the method breaks through the limitation of an experiment in the aspect of quantitative characterization of the starting amount of a grain size deformation mechanism, and meanwhile the problem that a conventional simulation method is large in error under the grain size is solved. Through deep fusion of experiments and simulation, the quantitative analysis precision of the deformation mechanism is remarkably improved, and a powerful technical support is provided for research of the microcosmic plastic deformation mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of microscopic plastic deformation and crystal plasticity finite element simulation, and in particular to a method for quantitatively revealing the activation amount of a grain-scale deformation mechanism. Background Art

[0002] The macroscopic mechanical properties of materials, such as strength, plasticity and formability, are essentially determined by the initiation and evolution of their microscopic plastic deformation mechanisms (such as slip, twinning, and phase transformation).

[0003] Currently, the study of the plastic deformation mechanisms of materials relies primarily on experimental characterization and numerical simulation. While advanced experimental characterization techniques, such as electron backscatter diffraction (EBSD), synchrotron X-ray diffraction, high-resolution transmission electron microscopy (HRTEM), and atomic force microscopy (AFM), can qualitatively reveal the activation type of deformation mechanisms, these methods can only qualitatively investigate the activation of deformation mechanisms and struggle to quantitatively analyze the degree of activation of each mechanism and its contribution to material properties. Numerical simulation methods, such as the viscoplastic self-consistent model (VPSC) and the crystal plasticity finite element method (CPFEM), can predict the activation of deformation mechanisms. However, because different grain orientations tend to activate different deformation mechanisms, and because individual grains vary in strength and shape, there is severe strain localization at the grain scale. This leads to significant deformation heterogeneity at the grain scale during plastic deformation. Simulations based on macroscopic deformation conditions often fail to accurately reflect the localized deformation behavior at the grain scale, resulting in significant errors in the predicted activation amount.

[0004] This technical bottleneck severely restricts the quantitative study of deformation mechanisms at the grain scale and also limits the in-depth understanding of the relationship between plastic deformation mechanisms and the mechanical and processing properties of materials. Therefore, it is urgent to develop a quantitative method that can combine real experimental data with high-precision simulations to accurately reveal the initiation behavior of deformation mechanisms at the grain scale and their impact on material properties. Summary of the Invention

[0005] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a method for quantitatively revealing the starting amount of the grain-scale deformation mechanism, so as to solve the problem that the prior art cannot accurately reflect the local deformation behavior of the grain scale, resulting in large errors in the starting amount prediction results.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: A method for quantitatively revealing the activation amount of grain-scale deformation mechanisms comprises the following steps: (1) According to the experimental requirements, cut the in-situ / quasi-in-situ sample, then grind the surfaces corresponding to the area where the sample is to be deformed flat. According to the experimental requirements, select a surface corresponding to the area where the sample is to be deformed as the observation surface, and polish the observation surface; (2) Select a scanning area on the sample observation surface, scan the scanning area using EBSD, and collect the initial grain orientation distribution data of the scanning area; (3) The sample is subjected to several plastic deformation treatments. After each plastic deformation, the scanning area described in step (2) is scanned again using EBSD to obtain grain orientation distribution data of different deformation states in the scanning area; (4) Denoise and divide the grain orientation distribution data of the initial state and different deformation states to determine the grain boundary distribution and the average orientation of each grain; (5) deriving the average orientation and position distribution information of the initial grains; the position distribution information is arranged in a matrix data set containing a number of identical cells by grain number, the same grain number represents the same grain, the size of the matrix data set is the same as the scanning area size, and the side length of each cell in the matrix data set is the same as the scanning step length of EBSD in step (2); (6) Process the grain orientation distribution data of different deformation states to retain the initial grain boundary, and use the triple boundary as the characteristic point to record the triple boundary coordinates of the initial state and different deformation states of the grain; (7) Match the coordinates of the trifurcated grain boundaries of the initial state and the grains with different deformation states, calculate the displacement of the trifurcated grain boundaries of the grains with different deformation states relative to the trifurcated grain boundaries of the corresponding initial state grains, and derive the coordinate position of the trifurcated grain boundaries of the initial state grains and the displacement of the trifurcated grain boundaries of the grains with different deformation states relative to the trifurcated grain boundaries of the corresponding initial state grains; (8) Using finite element software, a three-dimensional finite element model is established based on the size of the scanned area in step (2), and the surface of the finite element model is divided into a number of finite element units of the same size, wherein the size of the finite element unit is the same as the unit cell in the matrix data set; (9) Overlapping the matrix data set with grain numbers in step (5) with the finite element model. After overlapping, the finite element units corresponding to the same grain number are set as a set, thereby obtaining several sets. Then, material properties are assigned to these sets based on the average orientation of the corresponding initial grains, and a finite element model based on the real microstructure is constructed. (10) Using the coordinate position of the trifurcated grain boundary of the initial state grain in step (7), the corresponding unit node in the finite element model is queried, and the displacement of the grains of different deformation states relative to the initial state grain is assigned to the corresponding unit node; (11) Submit the finite element model obtained in step (10) for calculation in the finite element software, select the starting amount of each deformation mechanism in the calculation result file, and obtain the cumulative shear strain distribution diagram of each deformation mechanism under different strain amounts. Based on the obtained distribution diagram, the starting amount of each deformation mechanism at the grain scale can be read.

[0007] Furthermore, in step (4), the grain division is performed based on a grain boundary orientation difference of 10 degrees.

[0008] Furthermore, the EBSD scanning parameters in step (2) and step (3) are the same.

[0009] Furthermore, in step (3), the plastic deformation includes stretching, compression, bending or torsion.

[0010] Furthermore, in step (1), the sample is a polycrystalline material.

[0011] Furthermore, in step (7), the coordinate matching method of the trifurcated grain boundary includes manual matching, matching by coding based on the shape context method or the Hungarian algorithm.

[0012] Furthermore, in step (7), after matching, the triple boundaries of the initial state and the different modified grains are aligned, and then the displacement of the triple boundaries of the different modified grains relative to the triple boundaries of the corresponding initial state grains is calculated. By the alignment process, the overall morphology of the modified grains can be kept roughly in the original position, making it easier for researchers to observe.

[0013] Furthermore, the centering process involves overlaying the triple boundary distribution maps of the initial and differently deformed grains, and then using rigid body rotation and translation to bring the coordinates of the triple boundaries of the initial and differently deformed grains closer together. This rigid body rotation and translation can change the relative displacement of the sample before and after deformation without affecting the strain distribution (i.e., without affecting the relative position of the triple boundaries under the same state).

[0014] Furthermore, in step (8), the finite element software includes ABAQUS, ANASYS or DEFORM.

[0015] Furthermore, the deformation mechanism includes one or more of slip, twinning or phase change.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This paper, by deeply integrating in-situ / quasi-in-situ electron backscatter diffraction (EBSD) experiments with crystal plasticity finite element simulation (CPFEM), provides an innovative method for quantitatively studying the initiation of deformation mechanisms at the grain scale. Compared with conventional experimental methods, this method not only directly obtains the quantitative initiation of various deformation mechanisms (such as slip, twinning, and phase transformation), but also incorporates real grain deformation data (such as grain orientation and triple boundary displacement) to construct a finite element model. This method fully accounts for the heterogeneity of grain-scale deformation and can more realistically reflect grain-scale deformation behavior. This provides reliable quantitative support for the study of microscopic deformation mechanisms and addresses the problem of existing technologies that cannot accurately reflect local deformation behavior at the grain scale, resulting in large errors in initiation prediction results. This method provides a high-precision theoretical basis for the optimized design of material mechanical and processing properties, and has important scientific significance and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is the overall flow chart of the method of the present invention; Figure 2 Graphs showing grain orientation distributions in the initial state (a) and the modified state (b) in an embodiment of the present invention; Figure 3 Schematic diagram of the three-pronged grain boundary matching in an embodiment of the present invention (a: initial state, b: deformed state, c: matching relationship, d: displacement modulus); Figure 4 Schematic diagram of the finite element model and triple grain boundary displacement loading in an embodiment of the present invention; (a) finite element model of the actual microstructure, (b) schematic diagram of the actual triple grain boundary displacement loading; Figure 5 Cumulative shear strain of each deformation mechanism at 3% strain for the example: (a) basal slip, (b) cylindrical slip, (c) conical slip, and (d) tensile twinning.

[0018] Figure 6 The figures are comparative analysis of the results (a, b) of the method of the present invention and the experimental results (c, d) of the prior art in the examples: (a) the distribution of basal slip shear strain obtained by the method of the present invention, (b) the basal slip variant identification result of the grains in the white frame in (a) obtained by the method of the present invention, (c) the slip trace identification result of the scanning image of the in-situ experimental result of the prior art, and (d) the basal slip variant identification result of the grains in the white frame in (a) obtained by the experimental result of the prior art. DETAILED DESCRIPTION

[0019] The specific implementation methods of the present invention are further described in detail below with reference to specific examples. Example

[0020] This embodiment provides a method for quantitatively studying the activation of deformation mechanisms at the grain scale, and takes the study of the activation of deformation mechanisms during the stretching process of AZ31 magnesium alloy hot-rolled plate along the rolling direction as an example to describe the specific implementation of the present invention in detail. Figure 1 As shown, the following steps are included: S1. Experimental Procedure (1) Cutting samples: In-situ tensile samples were cut from AZ31 magnesium alloy rolled plates. The gauge length of the tensile sample was 27 mm × 3 mm × 2 mm, and the tensile deformation direction was consistent with the rolling direction of the rolled plate.

[0021] (2) Polishing the sample: Polish the surfaces of the tensile sample corresponding to the area to be deformed to ensure that the surfaces of the area to be deformed are flat and smooth; then, according to the experimental needs, select a surface corresponding to the area to be deformed (the side with a larger area) as the observation surface, and perform electrolytic polishing on the observation surface so that a good EBSD characterization effect can be obtained later; the polishing liquid is commercial ACII polishing liquid, and the polishing parameters are: voltage 20V; temperature -20 o C; polishing time 90 s. The larger surface was chosen as the observation surface primarily because the tensile specimen is thin and prone to necking during deformation. The side surfaces (smaller surfaces) experience severe deformation, resulting in noticeable pits during testing. In contrast, the front surface (larger surface) of the tensile specimen exhibits more uniform deformation.

[0022] (3) Initial state EBSD calibration: The sample is mounted on the in-situ stretching stage, a scanning area is selected on the sample observation surface, and the scanning area is scanned using EBSD to collect the initial state grain orientation distribution data of the scanning area; the EBSD scanning parameters are: scanning step length of 1 μm, scanning area of 300 μm × 300 μm.

[0023] (4) Plastic deformation: The sample is subjected to tensile deformation, with the tensile direction consistent with the rolling direction of the plate and the tensile rate being 10 -3 mm / s, and the strain is 3%.

[0024] (5) Deformation EBSD calibration: The observation surface is scanned again using EBSD to collect the grain orientation distribution data of the deformed state when the strain is 3%. The scanning area and scanning parameters are the same as those in step (3). Although the tensile deformation has occurred, the changes caused by the stretching are very small. Therefore, the area change of the original scanning area caused by the stretching is negligible. The scanning area in this step is still the same as that in step (3).

[0025] S2. Data processing flow (1) The MTEX toolbox of MATLAB was used to perform noise reduction on the grain orientation distribution data of the initial and deformed states. Then, the grains were divided based on the grain boundary orientation difference of 10 degrees to determine the grain boundary distribution and the average orientation of each grain.

[0026] Figure 2 is the grain orientation distribution diagram under the initial state and the deformed state, Figure 2 The sample exhibits a typical equiaxed structure, with different grain orientations. A trifurcated boundary forms at the intersection of three grains, and the relative position of the trifurcated boundary to the grains remains unchanged before and after deformation. Furthermore, twins form within some grains after plastic deformation, creating new trifurcated boundaries.

[0027] (2) The average orientation and grain distribution position information of 128 grains in the initial state were exported from MATLAB software to txt files respectively; the average orientation of the grains was expressed by Euler angles, and the grain distribution position information was expressed by a 300 × 300 matrix data set arranged with grain numbers. The same grain number represents the same grain, and the size of the matrix data set is the same as the scanning area size.

[0028] (3) Merge the twins of the modified grains with the parent grains to avoid the addition of new triple boundaries. Use MATLAB software to derive the triple boundary coordinates of the initial and modified grains. The merging method can be to manually delete the generated twins in MATLAB software, or to write a small program embedded in MATLAB software to merge the twins through program execution; other existing merging methods can also be used.

[0029] Figure 3 (a) and (b) are the trifurcated grain boundary distribution diagrams of the initial and deformed grains, respectively.

[0030] (4) Using MATLAB software, a code was written based on the shape context method to achieve the corresponding matching of the initial and deformed grain trigeminal boundaries. In specific implementation, the corresponding matching of the initial and deformed grain trigeminal boundaries can also be achieved through manual matching. The specific operation is as follows: first, the coordinate value of each trigeminal boundary is marked in the initial and deformed trigeminal boundary distribution maps, and then the trigeminal boundaries in the two states are overlapped. Since the relative position relationship of the grains in the sample does not change before and after deformation, the matching relationship of each trigeminal boundary can be identified by the naked eye after overlapping, thereby obtaining the corresponding relationship of the coordinates of the trigeminal boundaries before and after deformation.

[0031] The matching relationship between the initial state and the deformed state triple boundary is as follows: Figure 3As shown in (c), it can be seen that most of the initial triple boundaries (red circles) are matched one-to-one with the deformed triple boundaries (blue squares) (the matching relationship is represented by a green short line), indicating that the correct matching relationship is obtained through the above process.

[0032] (5) The initial and deformed trifurcated grain boundaries are aligned, and the displacement of the deformed trifurcated grain boundaries is calculated based on the coordinate positions of the initial and deformed trifurcated grain boundaries after the processing. The coordinate positions of each trifurcated grain boundary in the initial state and the displacement of the trifurcated grain boundary caused by deformation are then derived. The alignment method is: after overlapping the trifurcated grain boundary distribution maps of the initial and deformed states, the initial and deformed trifurcated grain boundaries are aligned as much as possible through rigid body rotation and translation.

[0033] Figure 3 (d) is the displacement modulus caused by deformation, given by Figure 3 (d) It can be seen that the displacement of each triple boundary can be obtained through the above process, and there are significant differences in the displacement of each triple boundary. Conventional finite element simulation methods are difficult to accurately simulate this phenomenon.

[0034] S3. Crystal plasticity finite element model construction and simulation process (1) A three-dimensional crystal plasticity finite element model (size: 300 μm × 300 μm × 3 μm) was established in ABAQUS finite element software and divided into C3D8 elements with a side length of 1 μm.

[0035] (2) Based on the initial state grain distribution position information derived in step S2, the finite element unit is divided into 128 unit sets; and 128 material properties are established based on the average orientation of each initial state grain. The material properties are then assigned to the corresponding unit sets to construct a finite element model based on the real microstructure. The specific implementation method of dividing the unit set is: the 300*300 matrix data set with grain numbers obtained in step S2-(2) is overlapped with the finite element model. After overlapping, the finite element units corresponding to the same grain number are set as a unit set named grain number, with a total of 128 unit sets. The specific implementation method of establishing material properties based on the average orientation of the initial state grains is: the material properties include elements such as grain orientation, elastic constant, deformation system shear plane and shear direction. Among them, only the grain orientation is different between different grains, and the other material parameters remain the same. The grain orientation is obtained in step S2-(2), and the other material parameters can be obtained from relevant literature. A set of grain orientations and other material parameters are integrated and input into ABAQUS to obtain the material properties for a single grain, known as the grain number. The created material properties are then copied sequentially and the grain orientation modified to obtain the material properties for another grain. This method generates material properties for a total of 128 grains. Finally, in ABAQUS, each material property is assigned to a set of grain elements with the same grain number, completing the model based on the actual microstructure.

[0036] Figure 4 (a) Finite element model of the real microstructure, given by Figure 4 (a) It can be seen that the finite element model consistent with the actual microstructure was successfully established through the above method.

[0037] (3) Based on the initial state triple grain boundary coordinate information in step S2-(5), the corresponding triple grain boundary node is searched in the finite element model, and the actual measured deformation triple grain boundary displacement is assigned to the node. In specific implementation, the search method is: the initial state triple grain boundary coordinate information map is overlapped with the finite element model. After overlap, the position corresponding to the initial state triple grain boundary on the finite element model is the corresponding node.

[0038] like Figure 4 As shown in (b), the finite element node displacement based on the real triple grain boundary displacement was successfully established, and different displacements were applied to each triple grain boundary.

[0039] (4) The complete crystal plasticity finite element model is submitted to the UMAT subroutine for calculation. The activation amount of each deformation mechanism is selected in the calculation result file, that is, the cumulative shear strain distribution diagram of each deformation mechanism under 3% strain is obtained. Based on this distribution diagram, the activation amount of each deformation mechanism at the grain scale can be read. The UMAT subroutine can be a self-written UMAT subroutine or an open source UMAT subroutine in the prior art.

[0040] Figure 5 The cumulative shear strain distributions for four deformation mechanisms (basal slip, cylindrical slip, conical slip, and tensile twinning) are shown for a tensile strain of 3%. The figure shows that plastic deformation is primarily dominated by basal slip, with its cumulative shear strain significantly higher than that of the other mechanisms. Furthermore, a small amount of tensile twinning is observed to initiate at some grain boundaries, consistent with theoretical understanding of plastic deformation in magnesium alloys and literature reports. Furthermore, the simulation results quantitatively reveal the heterogeneity of the shear strain distribution for basal slip at the grain scale, reflecting the significant influence of grain orientation differences and local stress concentration on the initiation of the deformation mechanism.

[0041] To further verify the accuracy of the method of the present invention, Figure 6 The simulation results of the method of the present invention were compared with the results of conventional experiments (scanning electron microscope (SEM)). Figure 6 (a) shows the simulated basal slip shear strain distribution, Figure 6 (c) Slip trace identification results based on scanning electron microscopy (SEM). Experimental results indicate that basal slip is the dominant deformation mechanism, and the slip distribution of the simulation results is highly consistent with that of conventional experiments. The large number of grains experiencing basal slip in the simulation matches the conventional experimental results, and the shear strain distribution characteristics of the simulation results are consistent with the slip trace angle distribution observed in conventional experiments.

[0042] Basal slip has three slip systems. Since they share the same slip surface, their slip traces are indistinguishable in morphology. In order to analyze the initiation of slip variants in depth, Figure 6 (b) and Figure 6 (d) shows the Figure 6(a) Simulation and conventional experimental slip variant identification results for a single grain within the white frame. Based on the lattice rotation analysis method modified by slip traces, the slip traces are first identified through SEM images to confirm that the grain has initiated basal slip. Three possible directions of basal slip orientation rotation are then plotted based on the average grain orientation and overlaid with the local orientation distribution for analysis. The results show that the grain has simultaneously initiated basal slip variants with slip directions of [-2110] and [-12-10]. The results from conventional experiments are consistent with those from simulations, verifying that the proposed method can not only accurately identify the deformation mechanism type but also precisely reveal the actual initiated slip variant.

[0043] In the examples, by comparing the results obtained by the method of the present invention with the conventional experimental characterization data, it was found that the two showed a high degree of consistency in the type and distribution of deformation mechanism activation, which verified the reliability of the method of the present invention in revealing the activation amount of grain-scale deformation mechanism. In addition, the method of the present invention also combines the advantages of experiments and simulations to provide a more reliable quantitative tool for the study of micro-plastic deformation mechanisms. This method not only makes up for the shortcomings of traditional experimental methods in quantitative analysis, but also overcomes the error problem caused by conventional numerical simulation methods due to ignoring the grain-scale deformation heterogeneity. In summary, the method of the present invention achieves the accurate revelation of the activation amount of grain-scale deformation mechanism through the deep integration of experiments and simulations, and provides reliable technical support for the study of the micro-mechanical behavior of materials and performance optimization.

[0044] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the technical solutions. Those skilled in the art should understand that modifications or equivalent replacements of the technical solutions of the present invention that do not depart from the purpose and scope of the technical solutions of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A method for quantitatively revealing the activation amount of grain-scale deformation mechanism, characterized in that: The following steps are involved: (1) According to the experimental requirements, cut the in-situ / quasi-in-situ sample, then grind the surfaces corresponding to the area where the sample is to be deformed flat. According to the experimental requirements, select a surface corresponding to the area where the sample is to be deformed as the observation surface, and polish the observation surface; (2) Select a scanning area on the sample observation surface, scan the scanning area using EBSD, and collect the initial grain orientation distribution data of the scanning area; (3) The sample is subjected to several plastic deformation treatments. After each plastic deformation, the scanning area described in step (2) is scanned again using EBSD to obtain grain orientation distribution data of different deformation states in the scanning area; (4) Denoise and divide the grain orientation distribution data of the initial state and different deformation states to determine the grain boundary distribution and the average orientation of each grain; (5) deriving the average orientation and position distribution information of the initial grains; the position distribution information is arranged in a matrix data set containing a number of identical cells by grain number, the same grain number represents the same grain, the size of the matrix data set is the same as the scanning area size, and the side length of each cell in the matrix data set is the same as the scanning step length of EBSD in step (2); (6) Process the grain orientation distribution data of different deformation states to retain the initial grain boundary, and use the triple boundary as the characteristic point to record the triple boundary coordinates of the initial state and different deformation states of the grain; (7) Match the coordinates of the trifurcated grain boundaries of the initial state and the grains with different deformation states, calculate the displacement of the trifurcated grain boundaries of the grains with different deformation states relative to the trifurcated grain boundaries of the corresponding initial state grains, and derive the coordinate position of the trifurcated grain boundaries of the initial state grains and the displacement of the trifurcated grain boundaries of the grains with different deformation states relative to the trifurcated grain boundaries of the corresponding initial state grains; (8) Using finite element software, a three-dimensional finite element model is established based on the size of the scanned area in step (2), and the surface of the finite element model is divided into a number of finite element units of the same size, wherein the size of the finite element unit is the same as the unit cell in the matrix data set; (9) Overlapping the matrix data set with grain numbers in step (5) with the finite element model. After overlapping, the finite element units corresponding to the same grain number are set as a set, thereby obtaining several sets. Then, material properties are assigned to these sets based on the average orientation of the corresponding initial grains, and a finite element model based on the real microstructure is constructed. (10) Using the coordinate position of the trifurcated grain boundary of the initial state grain in step (7), the corresponding unit node in the finite element model is queried, and the displacement of the grains of different deformation states relative to the initial state grain is assigned to the corresponding unit node; (11) Submit the finite element model obtained in step (10) for calculation in the finite element software, select the starting amount of each deformation mechanism in the calculation result file, and obtain the cumulative shear strain distribution diagram of each deformation mechanism under different strain amounts. Based on the obtained distribution diagram, the starting amount of each deformation mechanism at the grain scale can be read.

2. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 1, characterized in that: In step (4), the grain division is performed based on a grain boundary orientation difference of 10 degrees.

3. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 1, characterized in that: The EBSD scanning parameters in steps (2) and (3) are the same.

4. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 1, characterized in that: In step (3), the plastic deformation includes stretching, compression, bending or torsion.

5. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 1, characterized in that: In step (1), the sample is a polycrystalline material.

6. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 1, characterized in that: In step (7), the coordinate matching methods of the trifurcated grain boundary include manual matching, matching by coding based on the shape context method or the Hungarian algorithm.

7. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 1, characterized in that: In step (7), after matching, the triple boundaries of the initial state and the grains with different deformation states are aligned, and then the displacement of the triple boundaries of the grains with different deformation states relative to the triple boundaries of the corresponding initial state grains is calculated.

8. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 7, characterized in that: The centering process is to overlap the trifurcated grain boundary distribution diagrams of the initial state and the grains with different deformation states, and then make the trifurcated grain boundary coordinates of the initial state and the grains with different deformation states approach each other as a whole through rigid body rotation and translation.

9. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 1, characterized in that: In step (8), the finite element software includes ABAQUS, ANASYS or DEFORM.

10. The method for quantitatively revealing the activation amount of grain-scale deformation mechanism according to claim 1, characterized in that: The deformation mechanism includes one or more of slip, twinning or phase transformation.

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